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Data rotation improves genomotyping efficiency
Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Lübeck, Germany .ORCID iD: 0000-0002-7173-5579
DivisiÕn de MicrobiologÌa, Universidad Miguel Hernandez, Alicante, Spain.
Department of Molecular Evolution, Evolutionary Biology Center, Uppsala University, Uppsala, Sweden .
Department of Molecular Evolution, Evolutionary Biology Center, Uppsala University, Uppsala, Sweden .
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2005 (English)In: Biometrical Journal, ISSN 0323-3847, E-ISSN 1521-4036, Vol. 47, no 4, 585-98 p.Article in journal (Refereed) Published
Abstract [en]

Unsequenced bacterial strains can be characterized by comparing their genomic DNA to a sequenced reference genome of the same species. This comparative genomic approach, also called genomotyping, is leading to an increased understanding of bacterial evolution and pathogenesis. It is efficiently accomplished by comparative genomic hybridization on custom-designed cDNA microarrays. The microarray experiment results in fluorescence intensities for reference and sample genome for each gene. The log-ratio of these intensities is usually compared to a cut-off, classifying each gene of the sample genome as a candidate for an absent or present gene with respect to the reference genome. Reducing the usually high rate of false positives in the list of candidates for absent genes is decisive for both time and costs of the experiment. We propose a novel method to improve efficiency of genomotyping experiments in this sense, by rotating the normalized intensity data before setting up the list of candidate genes. We analyze simulated genomotyping data and also re-analyze an experimental data set for comparison and illustration. We approximately halve the proportion of false positives in the list of candidate absent genes for the example comparative genomic hybridization experiment as well as for the simulation experiments.

Place, publisher, year, edition, pages
Berlin, Germany: Akademie Verlag, 2005. Vol. 47, no 4, 585-98 p.
Keyword [en]
Comparative genomic hybridization, microarray, false discovery proportion, data transformation
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:oru:diva-40645DOI: 10.1002/bimj.200410160ISI: 000231492300014PubMedID: 16161813Scopus ID: 2-s2.0-24144473646OAI: oai:DiVA.org:oru-40645DiVA: diva2:778047
Available from: 2015-01-09 Created: 2015-01-09 Last updated: 2015-03-17Bibliographically approved

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CiteExportLink to record
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